Which AI models and platforms does Kombai support?

Updated

Kombai runs as a desktop app on macOS, Windows, and Linux, and as an extension inside VS Code and Cursor. For model choice, the site lists a selector with Auto plus named options: Kombai Fable 5.1, Anthropic Opus 5.5, Anthropic Grok 4.7, xAI Kimi K3, Moonshot AI GPT Image 2, and Image OpenAI. Because model lineups and platform builds change, treat the official site as the source of truth before you commit.

Platforms Kombai runs on

Kombai is distributed as a downloadable app and as editor extensions, so you can pick the environment that matches how you already work.

Environment How you use it Typical fit
macOS Desktop app Design-heavy work on a Mac
Windows Desktop app Teams standardized on Windows
Linux Desktop app Developers on Linux workstations
VS Code Extension Editing and shipping frontend in-editor
Cursor Extension AI-assisted coding workflows

The site states 600K+ installs and counting, and lists availability across these five targets. If your team works entirely in one editor, the extension route keeps design and code in the same loop rather than switching apps.

Model options inside Kombai

Kombai exposes a model selector rather than locking you to a single backend. The listed choices are:

  • Auto — lets Kombai pick, useful when you don't want to think about model routing per task.
  • Kombai Fable 5.1 — Kombai's own option.
  • Anthropic Opus 5.5
  • Anthropic Grok 4.7
  • xAI Kimi K3
  • Moonshot AI GPT Image 2
  • Image OpenAI

One practical note from the site's own framing: Kombai says you can "go beyond design slop, even with lower-cost models." That matters if you're choosing a model on cost — the claim is that design quality comes from Kombai's taste layer and repo context, not solely from the most expensive model. Treat that as a product claim to test on your own tasks, not a guarantee.

How to choose a model

There's no single correct pick. A workable approach:

  1. Start with Auto so you can see baseline output without tuning.
  2. When a task needs stronger reasoning or more polished design decisions, switch to a named model and compare on the same prompt.
  3. Keep the model constant across a batch of similar tasks so differences you see come from the task, not the model.

The site doesn't publish per-model pricing or rate limits, so cost comparisons between models aren't something you can settle from the page alone.

What stays consistent across models

Model choice affects generation, but Kombai's stated differentiators sit outside the model:

  • Creative Taste — identifies the key design decisions for each task and makes deliberate choices instead of AI defaults.
  • Infinite Canvases — explore and iterate on ideas before they touch production code.
  • Deep Product Context — reuses components, tokens, and hooks from your repo, npm package, or Storybook.
  • Any Model — the model selector itself.

So switching models doesn't reset your design system or repo context; those carry into new work regardless of which model you pick.

Before you decide

Confirm two things on the official site, since both can change:

  • The current model list — the selector shown here reflects what the page lists now.
  • The current platform builds — download links and editor support are updated over time.

If your question is really "will it fit my stack," the platform table above answers the environment half, and the model list answers the generation half. For anything version-specific, check kombai.com directly rather than relying on a snapshot.